Sr Data Scientist, AI/ML

Senior Data Scientist, AI & ML Location - **New York, NY (hybrid 3 Days per Week)** Position Overview We are seeking a Senior Data Scientist to join a growing Artificial Intelligence & Data organization focused on accelerating enterprise AI adoption and delivering transformative business outcomes. This role will support the development and deployment of advanced AI solutions spanning traditional Machine Learning, Generative AI, and Agentic AI use cases that improve customer, employee, and operational experiences.

The ideal candidate combines strong data science fundamentals with hands-on experience developing AI-powered applications, LLM solutions, and cloud-native machine learning systems. This individual will partner closely with business stakeholders, product teams, engineers, and technology leaders to build scalable AI solutions that drive measurable business value.

Key Responsibilities AI & Machine Learning Development

• Design, develop, and deploy AI and machine learning solutions aligned to strategic business objectives and enterprise AI initiatives.
• Execute key components of the Model Development Life Cycle (MDLC), including data exploration, feature engineering, model development, validation, deployment, and performance monitoring.
• Build and optimize predictive models using traditional machine learning and advanced AI techniques.
• Support development of agentic AI solutions that automate business processes while incorporating governance, safety guardrails, and human-in-the-loop controls.

Generative AI & Agentic AI Solutions

• Design and implement LLM-powered applications utilizing Retrieval-Augmented Generation (RAG), vector databases, embeddings, prompt orchestration, and evaluation frameworks.
• Develop and refine AI agents that improve workflow automation, decision support, and business productivity.
• Partner with AI Engineers to integrate AI capabilities into enterprise applications, APIs, and workflow platforms.
• Build lightweight prototypes and user-facing applications using tools such as Streamlit to accelerate solution validation and adoption.

Cloud & Platform Engineering

• Develop and deploy AI solutions leveraging cloud platforms including AWS and GCP.
• Utilize modern data platforms such as Snowflake and Databricks to support scalable AI and analytics workloads.
• Collaborate with MLOps and engineering teams to implement CI/CD, monitoring, testing, and governance best practices.
• Ensure AI solutions are secure, scalable, reliable, and aligned with enterprise architecture standards.

Stakeholder Collaboration & Innovation

• Partner with business leaders, product managers, engineers, and data teams to identify opportunities for AI-driven value creation.
• Translate complex analytical findings into actionable business recommendations.
• Communicate technical concepts, trade-offs, and outcomes effectively to both technical and non-technical stakeholders.
• Stay current on emerging AI technologies, industry trends, and best practices while contributing thought leadership across the organization.

Required Qualifications

• Master’s degree or higher in Computer Science, Data Science, Machine Learning, Artificial Intelligence, Statistics, Mathematics, Engineering, or a related quantitative discipline.
• 5+ years of experience applying Data Science, Machine Learning, and AI techniques to real-world business problems.
• Strong programming skills in Python and SQL.
• Experience with machine learning model development, validation, deployment, and monitoring.
• Experience with cloud platforms such as AWS and/or GCP, including AI/ML services.
• Experience working with modern data platforms such as Snowflake and Databricks.
• Working knowledge of Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), embeddings, vector stores, and agentic AI frameworks.
• Strong understanding of machine learning concepts including supervised learning, unsupervised learning, feature engineering, cross-validation, model evaluation, and optimization.
• Familiarity with software engineering best practices including Git, testing, logging, and version control.
• Excellent communication, collaboration, and stakeholder management skills.

Preferred Qualifications

• Experience building and deploying production-grade Generative AI and Agentic AI solutions.
• Experience mentoring junior data scientists and technical team members.
• Experience within financi…